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检索条件"任意字段=International Conference on Advances in Computer Science and Engineering"

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Permissioned Blockchain Security Pqfabric from Quantum and Classical Attacks 1

Permissioned Blockchain Security Pqfabric from Quantum and C...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Tamilarasi, C. Bhavadrarani, K. Kittappa, Thiagarajan Subashini, N. Anitha, V. Vimalraj, E. B.S.Abdur Rahman Crescent Institute of Science & Technology Department of Computer Science and Engineering Chennai India V.S.B. Engineering College Department of Computer Science and Engineering Karur India Rajalakshmi Institute of Technology Department of Mathematics Chennai600124 India Sathyabama Institute of Science and Technology Department of Mathematics Chennai600119 India Panimalar Engineering College Department of CSE Poonamallee Chennai600123 India School of Computing Mohan Babu University Andhra Pradesh Tirupati India

ISBN: (纸本)9798331518578

Old style cryptographic techniques are genuinely compromised by the development of quantum computing, which requires the formation of safety ideal models that are impervious to quantum mistakes. A new permissioned blockchain security system called PqFabric is intended to oppose both traditional and quantum attacks. PqFabric ensures the validness, mystery, and respectability of exchanges in a quantum-empowered future by including post-quantum cryptographic techniques like hash-based and grid based marks. As opposed to ordinary blockchains, PqFabric utilizes a half breed agreement process that gets information trades and members characters by melding Byzantine Fault Tolerance (BFT) with quantum-safe encryption. The system gives protection against calculation based attacks by Shor and Grover, tending to huge imperfections in existing blockchain structures. Besides, when quantum-safe guidelines advance, its secluded plan empowers smooth enhancements. With this procedure, PqFabric is situated as a ground breaking answer for organizations and areas wishing to safeguard their blockchain networks from new cryptographic risks. © 2025 IEEE.

关键词： Quantum computers

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Stream Processing and Real Time Analytics in the Era of Data engineering 1

Stream Processing and Real Time Analytics in the Era of Data...

引用

1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Chintala, Sathishkumar Plano TX United States

ISBN: (纸本)9798331518578

The prevalence of increased streaming of data revolutionises organisations approach with stream processing and real time analytics through actionable and immediate insights in the generated data streams. Advancements in data engineering drives the stream processing and real time analytics. The present study explores the transformative impact of real time analytics by examining the major components in stream processing and real time analytics such as visualisation tools, in-memory storage, stream processing and data ingestion. It enables the decision-making using data, optimised operations and personalised user experience. The study examines the multinational retail corporations and video streaming services for data engineering. The major advantages are competitive and operational efficiencies enhanced customer experience and rapid insights on stream processing. The tremendous potential is highlighted for implementation of real time analytics and stream processing with integration complexities, skill gaps, privacy and security concerns, systems scalability, enhanced data quality and management of data volume. Stream processing engine is used for higher throughput and lower processing latency based on workload. © 2025 IEEE.

关键词： Data streams

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Optimizing of 6G Network Performance Through Machine Learning by Allocating Resources 1

Optimizing of 6G Network Performance Through Machine Learnin...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Agarwal, Ankita Thulasiram, Ramachandran Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Mechanical Engineering Ramnagar District Karnataka India

ISBN: (纸本)9798331518578

The impediments with 6G network construction have encouraged the activity of Machine Learning Resource Allocation Algorithms (MLRA). In terms of flexibility and ability utilisation., MLRA outperforms more normal algorithms. Using data on how the network is functioning, the algorithms can resolve how to deliver resources most efficiently. To confirm that properties are delivered accurately and capably, MLRA will be decisive as 6G networks are employed to a greater extent. Quickly reallocating unaccustomed resources to more creative consumers or apps is entity the algorithms are fit achievement. The expected GB speeds and a 1000x increase in illiteracy from 6G networks are intense. Smart talent allocation algorithms that can exactly and expeditiously readjust to changeful consumer demands and behaviours are essential for this. The change to 6G networks and the facilities they supply will not be likely without MLRA. © 2025 IEEE.

关键词： Queueing networks

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Flexible Hybrid Electronics for Printing of Nano and Chip Scale Structures 1

Flexible Hybrid Electronics for Printing of Nano and Chip Sc...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Singh, Neelima Gupta, Radha Singh, Rakesh Kumar Shruthi, T.S. Gupta, Parbhat Singhal, Abhinav Uttaranchal University Department of Computer Science and Engineering Dehradun India Dayananda Sagar College of Engineering Department of Mathematics Bangalore560078 India IIMT College of Engineering U.P. Greater Noida India Nitte Meenakshi Institute of Technology Department of Mathematics Karnataka Bangalore India SRM Institute of Science and Technology Delhi NCR Campus Ghaziabad Modinagar India Tula's Institute Department of Computer Science and Engineering Dehradun248197 India

ISBN: (纸本)9798331518578

Adaptable sensors, circuits, and substrates are joined with unbending electronic parts to make adaptable flexible hybrid electronics (FHE). The printing of nanomaterials has benefits over the costly, multi-step, and blunder inclined cleanroom-based nano-microfabrication process, like expense adequacy, high-throughput, steadfastness, and adaptability. FHE usually consists of devices that range in size from nano to chip, and it might be difficult to integrate them using a standard procedure. The mix of ultrathin chips and nanowires (NWs) based electronic layers on a solitary substrate is shown here utilizing printed gadgets. The performance of the transistors on UTCs (ultrathin chips) is thoroughly studied in order to optimise the printing process. The adequacy of the printing system is affirmed by electrical information accumulated from 14 semiconductors on 3 unmistakable chips, which uncover next to no adjustment of execution following exchange printing. Building UV photodetectors utilizing DIW printing further exhibits the unrivaled grade nature of ZnO-NWs-put together electronic layers delivered with respect to a similar substrate. © 2025 IEEE.

关键词： Substrates

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AI-Driven Pedagogical Approaches in science Classrooms: Enhancing Digital Literacy and Learning Outcomes 1

AI-Driven Pedagogical Approaches in Science Classrooms: Enha...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Agrawal, Kajal Shahin, Asma B. Kumar, Sushil Shilpa Thamizharasan, S. Babu, T. Rajan Nath School of Business & Technology BCA MGMU Maharashtra Aurangabad India Maharashtra Institute of Technology Department of Emerging Sciences and Technology Maharashtra Aurangabad India Bhagat Phool Singh Mahila Vishwavidyalaya Department of Education Haryana Sonepat India Rajiv Gandhi College of Engineering and Technology Department of Computer Applications Puducherry India Rajiv Gandhi College of Engineering and Technology Department of Computer Science and Engineering Puducherry India

ISBN: (纸本)9798331518578

A high quality education in science classroom is crucial to foster equitable societal progress. However significant disparities for undeserved and marginalised community. Solutions using artificial intelligence bridges the cap through enhanced teaching methodologies to promote fair access to learning in science classroom. The present study explores the AI powered pedagogical approaches in science education. It examines the AI technologies including computer vision, natural language processing and machine learning techniques utilised for personalised learning delivering feedback at real time and boost a student engagement across various background. AI driven approaches can Taylor instruction to individual paces and learning style that ensure personalised support for every student. Platforms also offer additional assistance to learners facing challenges fostering equity and inclusivity in science education. Moreover, AI driven assessment tools provide teachers with valuable insights in student performance helping them to pinpoint the areas that requires improvement and targeted interventions. It enables collaborative learning environment that allows the student to interact regardless of geographical constraints thereby expanding access to science education with enhanced digital literacy and learning outcomes. © 2025 IEEE.

关键词： Federated learning

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Weibull probability distribution based on four years wind speed data using nine numerical methods

Weibull probability distribution based on four years wind sp...

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international conference on Innovation and Technological advances for Sustainability, ITAS 2023

作者： Badawi, Ahmed Ali, Hassan Ismail, Nasser A. Zyoud, Alhareth Yusoff, Siti Hajar Al-Rimawi, Ashraf Ghanem, Wasel College of Engineering Technology University of Doha for Science and Technology Doha Qatar Department of Electrical and Computer Engineering Birzeit University Birzeit Ramallah Palestine Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9781032803722

Wind energy potential can be estimated in a specific area using the Probability density function (PDF). PDF is used for the mean wind speed data on daily basis. This paper represents the analysis of the climatology of the mean wind speed data for Askalan city on the Mediterranean coastal plain of Palestine. A selection of the PDF had been implemented using nine numerical analysis methods to represent the cumulative distribution function and Weibull probability distribution. The two main parameters of the Weibull shape factor are k = 1.7848 and the scale factor parameter c = 4.3642 ms-1. The study assessment finds out the characteristics of wind energy conversion and results confirm that it can produce energy using small-scale wind turbines. Matlab software was used to implement the numerical methods and extract the wind characteristics. © 2025 The Author(s).

关键词： Windmill

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Semi-Supervised Deep Learning Based Method for Abnormality Detection in Videos 1

Semi-Supervised Deep Learning Based Method for Abnormality D...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Chaudhary, Deevesh Kumar, Sunil Dhaka, Vijaypal Singh Manipal University Jaipur Department of Data Science and Engineering Jaipur India Manipal University Jaipur Department of Computer Communication and Engineering Jaipur India

ISBN: (纸本)9798331518578

Anomaly detection refers to recognition of events different from normal ones for example road accident, fight, robbery, arsenal etc. Anomaly identification in real world surveillance videos is an important application of computer vision. The work proposed in the paper detects anomalous events in surveillance videos dataset and is based upon semi supervised deep learning model. We trained the model using UCF Crime dataset that consists of 950 normal videos and 950 anomalous videos. The anomaly videos in the dataset consists of 13 different types of anomalies such as Abuse, arrest, explosion, fight etc. that generally occur in real life. The anomaly in the dataset is labelled at video level and not at a specific frame in a video to define the semi supervised nature of learning paradigm. The extracted 3D features from dataset are fed into the multilayered deep learning model. Experimental results show that our approach has significant improvement over state-of-the-art approaches for anomaly detection in surveillance videos. The accuracy of model comes out to be 83.96 percent, that is improvement over other methods. © 2025 IEEE.

关键词： Self-supervised learning

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Machine Learning for Wireless Network Optimization: Algorithms and Applications for Adaptive Communication 1

Machine Learning for Wireless Network Optimization: Algorith...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Srinivas, Madhira Surya, S. Thakar, Prachi Deepak Jain, Amit Kumar Department of Computer Science & Engineering Hyderabad501301 India Chennai600116 India KJ college of Engineering & Management Research Department of Computer Engineering Pune India Poornima University Department of Electrical & Electronics Engineering Rajasthan Jaipur303905 India

ISBN: (纸本)9798331518578

This project looks into the possibility of applying machine learning to optimize wireless networks for adaptive communication. Using 5G resource data, it applies preprocessing, exploratory analysis, and visualization to identify key trends: signal strength, latency, and bandwidth utilization. Machine learning algorithms predict resource allocation based on latency-sensitive and bandwidth-demanding applications. The approach emphasizes energy efficiency, scalability, and service quality, and dynamically adjusts communication strategies to meet diverse network demands. The findings indicate the machine learning importance in enhancing elasticity and robustness in a wireless network and its general function. © 2025 IEEE.

关键词： 5G Optimization Adaptive Communication Bandwidth Data Pre-processing EDA Energy Efficiency Latency Machine Learning Network Elasticity Predictive Models Resource Allocation Scalability Signal Strength Wireless Networks

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AI-Driven Decision Support Systems for Project Management in Automobile engineering 1

AI-Driven Decision Support Systems for Project Management in...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Vasudevan, M. Kumar, B. Senthil Deevi, Durga Praveen More, Amrita Baid Huddar, Vikrant Turdialiev, Mukhammad Ali School of Management Hindustan Institute of Technology & Science Tamil Nadu Chennai India Hindustan Institute of Technology & Science Department of School of Management Tamil Nadu Chennai India O2 Technologies Inc CA United States Medi-Caps University Department of Management Studies Madhya Pradesh Indore India Mumbai University Department of Management Studies India Tashkent state university of law Department of Private International Law Tashkent Uzbekistan

ISBN: (纸本)9798331518578

The integration of artificial intelligence in project management with revolutionize engineering processes like automobile. The present study explores the impact of artificial intelligence in decision support system to optimise the project workflow with improved decision making and prediction of potential bottlenecks in automotive engineering. The technology driven decision support system includes natural language processing predictive analytics and machine learning examined for product innovation time management and cost production. The study discusses about the challenges in adaptability of artificial intelligence data security and system integration in the complex environment. The real-world applications are analysed for highlighting the ai driven decision support system to enhance competitiveness and agility in automobile engineering for project management. The study emphasises the potentiality of artificial intelligence in redefining the conventional engineering practises for data driven and smarter decision making in automotive sector. © 2025 IEEE.

关键词： Project management

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A Comparative Study of Data Structure for Efficient Query Processing 1

A Comparative Study of Data Structure for Efficient Query Pr...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kumar, Ankit Chilluri, Venkata Suresh Babu Sharma, Chandani Singh, Aniket Chandigarh University Department of Computer Science and Engineering Mohali140413 India Intuit Inc. Intuit Inc. Mountain ViewCA94043 United States CSE Department Mullana Haryana Ambala India Veer Madho Singh Bhandari Uttarakhand Technical University Department of Computer Science and Engineering India

ISBN: (纸本)9798331518578

Organisations are flooded with enormous amounts of data from many sources in the big data era. Effective query processing strategies are crucial for deriving significant insights and guiding well-informed judgements. MapReduce and other big data analytical tools have emerged as key concerns for numerous businesses and research teams. At the moment, similar tasks are submitted repeatedly using multi-queries that are converted into MapReduce jobs. Therefore, taking use of these related tasks may present opportunities to avoid performing MapReduce calculations repeatedly. Since then, other analyses have focused on the sharing possibility to improve multi-query processing. Therefore, the primary goal of this work is to thoroughly examine and distinguish between two predicate-based filter-based sharing opportunity strategies that are already in use: relaxed MRShare and MRShare. As far as predicate-based filters among multi-query questions, the relaxed MRShare technique performs noticeably better than the MRShare for shared data, according to a comparative study conducted using the TPC-H benchmark. © 2025 IEEE.

关键词： MapReduce

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